Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
18
datasets available to search
ShareScore release 0.9.0
Dataset results
18 results for “habitat modification”
FIGURE 3 in Habitat modification driven by land use as an environmental filter on the morphological traits of neotropical stream fish fauna
FIGURE 3 | Representation of significant associations (p <0.05) identified by the fourth-corner method in the factorial map of the RLQ analysis. Red denotes a positive relationship between morphological traits and environmental variables, blue indicates a negative relationship, and grey represents nonsignificant relationships. Codes: Cond: Conductivity, Rock: Rocky substrate, Woody: Woody debris, Turb: Turbidity, Backw: Backwater, DO: Dissolved Oxygen, Temp: Temperature. See acronyms for the morphological traits in Tab. S3.
FIGURE 1 in Habitat modification driven by land use as an environmental filter on the morphological traits of neotropical stream fish fauna
FIGURE 1 | Study area. Location of sampling sites according with land use covers: S1 -Manoel Gomes, S2 - Pedregulho, S3 - Arquimedes, S4 - Bom Retiro, S5 - Rio da Paz, S6 - Nene, S7 - Cascavel, S8 - Afluente do Quati, and S9 - Quati.
FIGURE 2 in Habitat modification driven by land use as an environmental filter on the morphological traits of neotropical stream fish fauna
FIGURE 2 | Relationship between morphological traits and environmental variables of the first two axes of the RLQ of the species along the lower Iguaçu River. The figures of the fish were added to illustrate the species. Codes: Woody: Woddy debris, Cond: Conductivity, Rocky: Rocky substrate, Turb: Turbidity, Backw: Backwater, DO: Dissolved Oxygen, Temp: Temperature, Anc: Ancystrus sp., Syn: Synbranchus sp., Hyp: Hypostomus sp., Hep: Heptapterus sp., Cam: Cambeva sp., Cor: Corydoras sp., Rha: Rhamdia sp., Geo: Geophagus sp., Ast: Astyanax sp., Psa: Psalidodon sp., Bry: Bryconamericus sp., Gym: Gymnotus sp., Hop: Hoplias sp., Pha: Phalloceros sp., Poe: Poecilia sp.
Effects of habitat modification on a tritrophic cascade in a lowland tropical rainforest
<b>Description: </b><p>The impact of anthropogenic disturbance of tropical rainforests on ecosystem processes is poorly understood. In this study I investigate how habitat modification in tropical rainforests may mediate a tritrophic cascade with resultant effects on herbivory, a key ecosystem process. I adopt a stepwise approach through the trophic levels, assessing the relationships between forest quality and the bird community assemblage, and corresponding impacts on predation rates and herbivory. I measured the bird community across a forest quality gradient, surveying 24 sites within a modified lowland tropical rainforest in Borneo. At each sampling location I established two treatments, one using a large (2 x 2 x 1.5m) cage designed to exclude vertebrates, and the second a control where no vertebrate exclusion was in place. I measured predation rates using dummy caterpillars, and herbivory rates on selected leaves in each treatment at all sampling locations. I used piecewise structural equation modelling to develop a path model between predictor and response variables. I established a significant pathway between increasing forest quality, increased richness of the bird community and higher vertebrate predation rates. Conversely, invertebrate predation rates declined with increasing forest quality. The effect of increasing forest quality did not mediate a trophic cascade bringing about an increase in herbivory. However, the effect of vertebrate exclusion mediated a trophic cascade and an increase in herbivory in higher forest quality, where invertebrate predation levels are lower. The results of the study therefore reflect the dampening of the tritrophic cascade across a forest quality gradient, and high functional redundancy in predatory function in forests of low quality. The study also highlights the importance of avian predatory function in forests of higher quality. A reduction in large vertebrate predators in undisturbed tropical rainforests may therefore result in cascading effects on herbivory, which may in turn have implications for primary productivity and nutrient cycling. These findings have significant implications for tropical forest conservation and management. Further research should place emphasis on addressing the effects of the loss of apex predators on key ecosystem processes.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/201"><b>The effects of habitat modification on a tritrophic cascade in a lowland tropical rainforest</b></a></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (SABC) (Research licence JKN/MBS.1000-2/2 JLD.8 (66))</li><li>Sabah Biodiversity Centre (SABC) (Research licence JKM/MBS.1000-2/2 JLD.8 (61) )</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3981222">here</a></p><p><b>Files: </b>This dataset consists of 2 files: FraserExclusionPlots_AFedit_150820.xlsx, FraserAdam_TFE_2019_SAFE_AudioFiles.zip</p><p><b>FraserExclusionPlots_AFedit_150820.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>Bird point counts</b> (described in worksheet PointCounts)</p><p>Description: Repeated bird point counts at all sites</p><p>Number of fields: 89</p><p>Number of data rows: 72</p><p>Fields: </p><ul><li><b>Visit_Code</b>: Unique site x replicate code (Field type: id)</li><li><b>Plot</b>: SAFE Project plot ID (Field type: location)</li><li><b>Visit</b>: Visit number (Field type: replicate)</li><li><b>Date</b>: Date of point count (Field type: date)</li><li><b>Time_Start</b>: Time at start of point count (Field type: time)</li><li><b>Time_Finish</b>: Time at end of point count (Field type: time)</li><li><b>Weather</b>: Observations on weather conditions (Field type: comments)</li><li><b>Ashy.tailorbird</b>: Count of individuals (Field type: abundance)</li><li><b>Asian.fairy.bluebird</b>: Count of individuals (Field type: abundance)</li><li><b>Asian.paradise.flycatcher</b>: Count of individuals (Field type: abundance)</li><li><b>Asian.red.eyed.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Banded.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Banded.bay.cuckoo</b>: Count of individuals (Field type: abundance)</li><li><b>Black.and.red.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Black.and.yellow.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Black.capped.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Black.headed.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Black.headed.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Black.naped.monarch</b>: Count of individuals (Field type: abundance)</li><li><b>Blue.eared.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Blue.headed.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Bold.striped.tit.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Bornean.banded.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Bornean.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Bronzed.drongo</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.fulvetta</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.backed.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.throated.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Bushy.crested.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.backed.scimitar.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.munia</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.rumped.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.winged.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Collared.kingfisher</b>: Count of individuals (Field type: abundance)</li><li><b>Common.emerald.dove</b>: Count of individuals (Field type: abundance)</li><li><b>Cream.vented.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Crested.fireback</b>: Count of individuals (Field type: abundance)</li><li><b>Crimson.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Dark.necked.tailorbird</b>: Count of individuals (Field type: abundance)</li><li><b>Diards.trogon</b>: Count of individuals (Field type: abundance)</li><li><b>Dusky.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Fiery.minivet</b>: Count of individuals (Field type: abundance)</li><li><b>Fluffy.backed.tit.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Gold.whiskered.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Great.argus</b>: Count of individuals (Field type: abundance)</li><li><b>Greater.green.leafbird</b>: Count of individuals (Field type: abundance)</li><li><b>Greater.racket.tailed.drongo</b>: Count of individuals (Field type: abundance)</li><li><b>Green.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Grey.headed.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Helmeted.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Hooded.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Lesser.green.leafbird</b>: Count of individuals (Field type: abundance)</li><li><b>Little.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Long.billed.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Malaysian.blue.flycatcher</b>: Count of individuals (Field type: abundance)</li><li><b>Moustached.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Orange.bellied.flowerpecker</b>: Count of individuals (Field type: abundance)</li><li><b>Pied.fantail</b>: Count of individuals (Field type: abundance)</li><li><b>Plain.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Plaintive.cuckoo</b>: Count of individuals (Field type: abundance)</li><li><b>Puff.backed.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Purple.naped.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Raffless.malkoha</b>: Count of individuals (Field type: abundance)</li><li><b>Red.bearded.bee.eater</b>: Count of individuals (Field type: abundance)</li><li><b>Red.naped.trogon</b>: Count of individuals (Field type: abundance)</li><li><b>Red.throated.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Rhinoceros.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.collared.kingfisher</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.crowned.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.fronted.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.tailed.tailorbird</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.tailed.shama</b>: Count of individuals (Field type: abundance)</li><li><b>Scarlet.rumped.trogon</b>: Count of individuals (Field type: abundance)</li><li><b>Short.tailed.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Short.toed.coucal</b>: Count of individuals (Field type: abundance)</li><li><b>Slender.billed.crow</b>: Count of individuals (Field type: abundance)</li><li><b>Sooty.capped.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Spectacled.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Spectacled.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Violet.cuckoo</b>: Count of individuals (Field type: abundance)</li><li><b>White.crowned.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>White.crowned.shama</b>: Count of individuals (Field type: abundance)</li><li><b>Woodpecker.sp.</b>: Count of individuals (Field type: abundance)</li><li><b>Wreathed.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.breasted.flowerpecker</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.crowned.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.rumped.flowerpecker</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.vented.bulbul</b>: Count of individuals (Field type: abundance)</li></ul></li><li><p><b>Leaf herbivory</b> (described in worksheet LeafHerbivory)</p><p>Description: Within each treatment, I tagged and numbered seven leaves. I chose a variation of leaf ages within each treatment, as recommended by Coley and Barone (1996). I measured leaf area on all tagged leaves at monthly intervals, as recommended by Coley and Barone (1996) and detailed in Harrison and Banks-Leite (2019), between March and May 2019. I calculated arthropod herbivory rate using ImageJ software (Schindelin et al. 2012) to determine the percentage leaf area lost (LAL) over time.</p><p>Number of fields: 9</p><p>Number of data rows: 336</p><p>Fields: </p><ul><li><b>Site</b>: SAFE Project plot ID (Field type: location)</li><li><b>Treatment</b>: Experimental treatment: inside or outside exclusion cage? (Field type: categorical)</li><li><b>Leaf</b>: ID number for each leaf (Field type: replicate)</li><li><b>DateFirstObs</b>: Date of first leaf observation (Field type: date)</li><li><b>LeafArea</b>: Leaf area at first observation (Field type: numeric)</li><li><b>DateFinalObs</b>: Date of final leaf observation (Field type: date)</li><li><b>FinalLeafArea</b>: Leaf area at last observation (Field type: numeric)</li><li><b>LostArea</b>: Area of leaf lost to herbivory (Field type: numeric)</li><li><b>PercentLostArea</b>: Percent of leaf area lost to herbivory (Field type: numeric)</li></ul></li><li><p><b>Insect predation data</b> (described in worksheet PredationData)</p><p>Description: I assessed predation rates on invertebrates by placing five plasticine dummy caterpillars within each treatment, at each sampling location. The methods were based on those described in Howe, Lövei and Nachman (2009) Roslin et al. (2017) and Roels, Porter and Lindell (2018). I placed five fresh plasticine caterpillars at least one metre apart from each other within the treatment and recovered the caterpillars after 14 days. I quantified predation attempts on each set of caterpillars within each treatment, following guidance on visual predator identification as per Low et al. (2014).</p><p>Number of fields: 9</p><p>Number of data rows: 144</p><p>Fields: </p><ul><li><b>Visit_Code</b>: Unique site x replicate code (Field type: id)</li><li><b>Plot</b>: SAFE Project plot ID (Field type: location)</li><li><b>Visit</b>: Visit number (Field type: replicate)</li><li><b>Date</b>: Date of point count (Field type: date)</li><li><b>Treatment</b>: Experimental treatment: inside or outside exclusion cage? (Field type: categorical)</li><li><b>Invertebrate</b>: Number of plasticine invertebrate mimics attacked by invertebrate predator (Field type: numeric)</li><li><b>Mammal</b>: Number of plasticine invertebrate mimics attacked by mammalian predator (Field type: numeric)</li><li><b>Bird</b>: Number of plasticine invertebrate mimics attacked by avian predator (Field type: numeric)</li><li><b>Other</b>: Number of plasticine invertebrate mimics attacked by predator that couldn't be identified (Field type: numeric)</li></ul></li></ol><p><b>FraserAdam_TFE_2019_SAFE_AudioFiles.zip</b></p><p>Description: Audio files recorded during points counts</p><p><b>Date range: </b>2019-03-04 to 2019-05-10</p><p><b>Latitudinal extent: </b>4.6815 to 4.7435</p><p><b>Longitudinal extent: </b>117.5396 to 117.5971</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Aves <br> -  -  -  -  Piciformes <br> -  -  -  -  -  Picidae <br> -  -  -  -  -  Ramphastidae <br> -  -  -  -  -  -  <i>Psilopogon</i> <br> -  -  -  -  -  -  -  <i>Psilopogon duvaucelii</i> <br> -  -  -  -  -  -  -  <i>Psilopogon chrysopogon</i> <br> -  -  -  -  -  -  -  <i>Psilopogon mystacophanos</i> <br> -  -  -  -  -  -  -  <i>Psilopogon henricii</i> <br> -  -  -  -  -  -  <i>Caloramphus</i> <br> -  -  -  -  -  -  -  <i>Caloramphus fuliginosus</i> <br> -  -  -  -  Coraciiformes <br> -  -  -  -  -  Alcedinidae <br> -  -  -  -  -  -  <i>Todiramphus</i> <br> -  -  -  -  -  -  -  <i>Todiramphus chloris</i> <br> -  -  -  -  -  -  <i>Actenoides</i> <br> -  -  -  -  -  -  -  <i>Actenoides concretus</i> <br> -  -  -  -  -  Meropidae <br> -  -  -  -  -  -  <i>Nyctyornis</i> <br> -  -  -  -  -  -  -  <i>Nyctyornis amictus</i> <br> -  -  -  -  Galliformes <br> -  -  -  -  -  Phasianidae <br> -  -  -  -  -  -  <i>Argusianus</i> <br> -  -  -  -  -  -  -  <i>Argusianus argus</i> <br> -  -  -  -  -  -  <i>Lophura</i> <br> -  -  -  -  -  -  -  <i>Lophura ignita</i> <br> -  -  -  -  Columbiformes <br> -  -  -  -  -  Columbidae <br> -  -  -  -  -  -  <i>Chalcophaps</i> <br> -  -  -  -  -  -  -  <i>Chalcophaps indica</i> <br> -  -  -  -  Passeriformes <br> -  -  -  -  -  Corvidae <br> -  -  -  -  -  -  <i>Corvus</i> <br> -  -  -  -  -  -  -  <i>Corvus enca</i> <br> -  -  -  -  -  Pellorneidae <br> -  -  -  -  -  -  <i>Pellorneum</i> <br> -  -  -  -  -  -  -  <i>Pellorneum capistratum</i> <br> -  -  -  -  -  -  <i>Alcippe</i> <br> -  -  -  -  -  -  -  <i>Alcippe brunneicauda</i> <br> -  -  -  -  -  -  <i>Trichastoma</i> <br> -  -  -  -  -  -  -  <i>Trichastoma malaccense</i> <br> -  -  -  -  -  -  <i>Malacopteron</i> <br> -  -  -  -  -  -  -  <i>Malacopteron magnirostre</i> <br> -  -  -  -  -  -  -  <i>Malacopteron magnum</i> <br> -  -  -  -  -  -  -  <i>Malacopteron affine</i> <br> -  -  -  -  -  Cisticolidae <br> -  -  -  -  -  -  <i>Orthotomus</i> <br> -  -  -  -  -  -  -  <i>Orthotomus ruficeps</i> <br> -  -  -  -  -  -  -  <i>Orthotomus atrogularis</i> <br> -  -  -  -  -  -  -  <i>Orthotomus sericeus</i> <br> -  -  -  -  -  Rhipiduridae <br> -  -  -  -  -  -  <i>Rhipidura</i> <br> -  -  -  -  -  -  -  <i>Rhipidura javanica</i> <br> -  -  -  -  -  Muscicapidae <br> -  -  -  -  -  -  <i>Trichixos</i> <br> -  -  -  -  -  -  -  <i>Trichixos pyrropygus</i> <br> -  -  -  -  -  -  <i>Cyornis</i> <br> -  -  -  -  -  -  -  <i>Cyornis turcosus</i> <br> -  -  -  -  -  -  <i>Copsychus</i> <br> -  -  -  -  -  -  -  <i>Copsychus stricklandii</i> <br> -  -  -  -  -  Dicaeidae <br> -  -  -  -  -  -  <i>Dicaeum</i> <br> -  -  -  -  -  -  -  <i>Dicaeum everetti</i> <br> -  -  -  -  -  -  -  <i>Dicaeum trigonostigma</i> <br> -  -  -  -  -  -  <i>Prionochilus</i> <br> -  -  -  -  -  -  -  <i>Prionochilus maculatus</i> <br> -  -  -  -  -  -  -  <i>Prionochilus xanthopygius</i> <br> -  -  -  -  -  Campephagidae <br> -  -  -  -  -  -  <i>Pericrocotus</i> <br> -  -  -  -  -  -  -  <i>Pericrocotus igneus</i> <br> -  -  -  -  -  Timaliidae <br> -  -  -  -  -  -  <i>Pomatorhinus</i> <br> -  -  -  -  -  -  -  <i>Pomatorhinus montanus</i> <br> -  -  -  -  -  -  <i>Cyanoderma</i> <br> -  -  -  -  -  -  -  <i>Cyanoderma erythropterum</i> <br> -  -  -  -  -  -  -  <i>Cyanoderma rufifrons</i> <br> -  -  -  -  -  -  <i>Stachyris</i> <br> -  -  -  -  -  -  -  <i>Stachyris maculata</i> <br> -  -  -  -  -  -  -  <i>Stachyris poliocephala</i> <br> -  -  -  -  -  -  <i>Macronus</i> <br> -  -  -  -  -  -  -  <i>Macronus ptilosus</i> <br> -  -  -  -  -  -  <i>Mixornis</i> <br> -  -  -  -  -  -  -  <i>Mixornis bornensis</i> <br> -  -  -  -  -  Eurylaimidae <br> -  -  -  -  -  -  <i>Eurylaimus</i> <br> -  -  -  -  -  -  -  <i>Eurylaimus javanicus</i> <br> -  -  -  -  -  -  -  <i>Eurylaimus ochromalus</i> <br> -  -  -  -  -  -  <i>Calyptomena</i> <br> -  -  -  -  -  -  -  <i>Calyptomena viridis</i> <br> -  -  -  -  -  -  <i>Cymbirhynchus</i> <br> -  -  -  -  -  -  -  <i>Cymbirhynchus macrorhynchos</i> <br> -  -  -  -  -  -  <i>Corydon</i> <br> -  -  -  -  -  -  -  <i>Corydon sumatranus</i> <br> -  -  -  -  -  Dicruridae <br> -  -  -  -  -  -  <i>Dicrurus</i> <br> -  -  -  -  -  -  -  <i>Dicrurus aeneus</i> <br> -  -  -  -  -  -  -  <i>Dicrurus paradiseus</i> <br> -  -  -  -  -  Estrildidae <br> -  -  -  -  -  -  <i>Lonchura</i> <br> -  -  -  -  -  -  -  <i>Lonchura atricapilla</i> <br> -  -  -  -  -  Pycnonotidae <br> -  -  -  -  -  -  <i>Pycnonotus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus brunneus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus atriceps</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus simplex</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus eutilotus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus erythropthalmos</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus goiavier</i> <br> -  -  -  -  -  Chloropseidae <br> -  -  -  -  -  -  <i>Chloropsis</i> <br> -  -  -  -  -  -  -  <i>Chloropsis sonnerati</i> <br> -  -  -  -  -  -  -  <i>Chloropsis cyanopogon</i> <br> -  -  -  -  -  Nectariniidae <br> -  -  -  -  -  -  <i>Aethopyga</i> <br> -  -  -  -  -  -  -  <i>Aethopyga siparaja</i> <br> -  -  -  -  -  -  <i>Anthreptes</i> <br> -  -  -  -  -  -  -  <i>Anthreptes malacensis</i> <br> -  -  -  -  -  -  -  <i>Anthreptes simplex</i> <br> -  -  -  -  -  -  <i>Arachnothera</i> <br> -  -  -  -  -  -  -  <i>Arachnothera everetti</i> <br> -  -  -  -  -  -  -  <i>Arachnothera longirostra</i> <br> -  -  -  -  -  -  -  <i>Arachnothera robusta</i> <br> -  -  -  -  -  -  -  <i>Arachnothera flavigaster</i> <br> -  -  -  -  -  -  <i>Kurochkinegramma</i> <br> -  -  -  -  -  -  -  <i>Kurochkinegramma hypogrammicum</i> <br> -  -  -  -  -  Irenidae <br> -  -  -  -  -  -  <i>Irena</i> <br> -  -  -  -  -  -  -  <i>Irena puella</i> <br> -  -  -  -  -  Pittidae <br> -  -  -  -  -  -  <i>Erythropitta</i> <br> -  -  -  -  -  -  -  <i>Erythropitta ussheri</i> <br> -  -  -  -  -  -  <i>Pitta</i> <br> -  -  -  -  -  -  -  <i>Pitta sordida</i> <br> -  -  -  -  -  Monarchidae <br> -  -  -  -  -  -  <i>Hypothymis</i> <br> -  -  -  -  -  -  -  <i>Hypothymis azurea</i> <br> -  -  -  -  -  -  <i>Terpsiphone</i> <br> -  -  -  -  -  -  -  <i>Terpsiphone paradisi</i> <br> -  -  -  -  Trogoniformes <br> -  -  -  -  -  Trogonidae <br> -  -  -  -  -  -  <i>Harpactes</i> <br> -  -  -  -  -  -  -  <i>Harpactes diardii</i> <br> -  -  -  -  -  -  -  <i>Harpactes kasumba</i> <br> -  -  -  -  -  -  -  <i>Harpactes duvaucelii</i> <br> -  -  -  -  Cuculiformes <br> -  -  -  -  -  Cuculidae <br> -  -  -  -  -  -  <i>Chrysococcyx</i> <br> -  -  -  -  -  -  -  <i>Chrysococcyx xanthorhynchus</i> <br> -  -  -  -  -  -  <i>Centropus</i> <br> -  -  -  -  -  -  -  <i>Centropus rectunguis</i> <br> -  -  -  -  -  -  <i>Cacomantis</i> <br> -  -  -  -  -  -  -  <i>Cacomantis sonneratii</i> <br> -  -  -  -  -  -  -  <i>Cacomantis merulinus</i> <br> -  -  -  -  -  -  <i>Rhinortha</i> <br> -  -  -  -  -  -  -  <i>Rhinortha chlorophaea</i> <br> -  -  -  -  Bucerotiformes <br> -  -  -  -  -  Bucerotidae <br> -  -  -  -  -  -  <i>Berenicornis</i> <br> -  -  -  -  -  -  -  <i>Berenicornis comatus</i> <br> -  -  -  -  -  -  <i>Anorrhinus</i> <br> -  -  -  -  -  -  -  <i>Anorrhinus galeritus</i> <br> -  -  -  -  -  -  <i>Rhyticeros</i> <br> -  -  -  -  -  -  -  <i>Rhyticeros undulatus</i> <br> -  -  -  -  -  -  <i>Buceros</i> <br> -  -  -  -  -  -  -  <i>Buceros rhinoceros</i> <br> -  -  -  -  -  -  <i>Rhinoplax</i> <br> -  -  -  -  -  -  -  <i>Rhinoplax vigil</i> <br> -  -  -  -  <i>Hydrornis</i> <br> -  -  -  -  -  <i>Hydrornis baudii</i> <br> -  -  -  -  -  <i>Hydrornis schwaneri</i> <br></div><p></p>
Hornbill abundance and breeding incidence in relation to habitat modification and fig fruit availability
<p>Asian hornbills are known to forage and breed in fragmented rainforests and agroforestry plantations in human‐modified landscapes adjoining contiguous protected forests. However, the factors influencing year‐round hornbill abundance, demography and tracking of key food resources such as wild fig <em>Ficus</em> fruits in modified habitats and protected forests remain poorly understood. We carried out monthly surveys of two species of high conservation concern, the Vulnerable Great Hornbill (GH, <em>Buceros bicornis</em>) and the endemic Malabar Grey Hornbill (MGH, <em>Ocyceros griseus</em>) for 15 months and monitored ripe fig fruit availability for 12 months along 11 line transects (total length 24 km) in shade‐coffee plantations and adjoining continuous rainforests in a protected area (PA) in the Anamalai Hills, Western Ghats, India. Both hornbill species used plantations and the PA year‐round but distance sampling density estimates were higher in the PA in both nesting (GH by 57%; MGH by 50%) and non‐nesting (GH by 53%; MGH by 144%) seasons. Relative to estimates from 2004 to 2005, mean GH density appeared stable or increasing, whereas MGH had declined by 39% in the PA and by 56% in plantations. Monthly encounter rate of both hornbills tended to be higher in the PA and that of MGH was also positively related to the density of fig trees with ripe fruit. Sex ratios of observed adult birds in the non‐nesting season were relatively even (GH) or slightly female‐biased (MGH), but became male‐biased in both species during the nesting season when females were confined in tree‐cavity nests. We used change in the adult sex ratio of observed birds from the non‐nesting to nesting season to estimate an index of the proportion of adult pairs breeding at any point within the season, providing the first such estimates for any hornbill species. The proportion of breeding pairs was higher in the PA (GH – 56%, MGH – 64%) than in the plantations (GH – 33%, MGH – 30%). Although hornbills use shade‐coffee plantations year‐round, partly due to fig fruit availability, differences in hornbill density and breeding incidence, as assessed from the sex ratios of observed adult birds, indicate that plantations are a sub‐optimal habitat for both species.</p>
The effects of habitat modification on the distribution and feeding ecology of Orthoptera 2015
<b>Description: </b><p>Postdoctoral project</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/4"><b>The effects of habitat modification on the distribution and feeding ecology of Orthoptera</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Australian Research Council (ARC Discovery Project, DP140101541)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=7011354">here</a></p><p><b>Files: </b>This consists of 1 file: Hardwick_Orthoptera_220811.xlsx</p><p><b>Hardwick_Orthoptera_220811.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Orthoptera assemblage composition data 2015</b> (described in worksheet OrthopteraAssem)</p><p>Description: Orthoptera assemblage composition data collected at the SAFE Project in 2015. Worksheet contains a site by morphospecies abundance matrix. Orthoptera were collected by sweep netting along a 100m transect at each location. Orthoptera were identified to family and seperated into morphospecies using identification guides. </p><p>Number of fields: 95</p><p>Number of data rows: 48</p><p>Fields: </p><ul><li><b>Date1</b>: Date of the first collection (Field type: date)</li><li><b>Date2</b>: Date of the second collection (Field type: date)</li><li><b>Location</b>: SAFE Project location (2nd order) (Field type: location)</li><li><b>Type</b>: Disturbance gradient (Field type: ordered categorical)</li><li><b>Collector</b>: First initial and last name of person who collected the sample (Field type: categorical)</li><li><b>ACRI01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI03_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI04_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI05_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI06_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI07_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI08_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI09_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI10_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI11_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI12_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI13_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI14_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI15_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI16_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI17_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI18_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI19_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>ACRI20_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR03_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR04_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR05_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR06_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR07_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR08_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR09_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR10_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR11_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR12_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR13_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR14_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR15_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR16_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR17_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR18_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR19_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR20_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TETR21_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL03_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL04_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL05_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL06_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL07_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL08_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL09_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL10_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL11_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL12_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL13_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL14_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL15_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL16_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL17_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL18_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL19_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL20_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>GRYL21_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>MOGO01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>MOGO02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRID01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRID02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRIG01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRIG02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRIG03_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRIG04_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRIG05_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>TRIG06_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID01_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID02_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID03_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID04_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID05_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID06_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID07_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID08_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID09_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID10_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID12_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID13_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID14_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID15_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID16_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID17_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID18_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li><li><b>UNID19_count</b>: Number collected along a 100m transect, twice sampled (Field type: abundance)</li></ul></li></ol><p><b>Date range: </b>2015-06-03 to 2015-08-14</p><p><b>Latitudinal extent: </b>4.6359 to 4.7509</p><p><b>Longitudinal extent: </b>116.9549 to 117.6257</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Arthropoda <br> -  -  -  Insecta <br> -  -  -  -  Orthoptera <br> -  -  -  -  -  [UNID01] <br> -  -  -  -  -  [UNID02] <br> -  -  -  -  -  [UNID03] <br> -  -  -  -  -  [UNID04] <br> -  -  -  -  -  [UNID05] <br> -  -  -  -  -  [UNID06] <br> -  -  -  -  -  [UNID07] <br> -  -  -  -  -  [UNID08] <br> -  -  -  -  -  [UNID09] <br> -  -  -  -  -  [UNID10] <br> -  -  -  -  -  [UNID12] <br> -  -  -  -  -  [UNID13] <br> -  -  -  -  -  [UNID14] <br> -  -  -  -  -  [UNID15] <br> -  -  -  -  -  [UNID16] <br> -  -  -  -  -  [UNID17] <br> -  -  -  -  -  [UNID18] <br> -  -  -  -  -  [UNID19] <br> -  -  -  -  -  Gryllidae <br> -  -  -  -  -  -  [GRYL01] <br> -  -  -  -  -  -  [GRYL02] <br> -  -  -  -  -  -  [GRYL03] <br> -  -  -  -  -  -  [GRYL04] <br> -  -  -  -  -  -  [GRYL05] <br> -  -  -  -  -  -  [GRYL06] <br> -  -  -  -  -  -  [GRYL07] <br> -  -  -  -  -  -  [GRYL08] <br> -  -  -  -  -  -  [GRYL09] <br> -  -  -  -  -  -  [GRYL10] <br> -  -  -  -  -  -  [GRYL11] <br> -  -  -  -  -  -  [GRYL12] <br> -  -  -  -  -  -  [GRYL13] <br> -  -  -  -  -  -  [GRYL14] <br> -  -  -  -  -  -  [GRYL15] <br> -  -  -  -  -  -  [GRYL16] <br> -  -  -  -  -  -  [GRYL17] <br> -  -  -  -  -  -  [GRYL18] <br> -  -  -  -  -  -  [GRYL19] <br> -  -  -  -  -  -  [GRYL20] <br> -  -  -  -  -  -  [GRYL21] <br> -  -  -  -  -  Acrididae <br> -  -  -  -  -  -  [ACRI01] <br> -  -  -  -  -  -  [ACRI02] <br> -  -  -  -  -  -  [ACRI03] <br> -  -  -  -  -  -  [ACRI04] <br> -  -  -  -  -  -  [ACRI05] <br> -  -  -  -  -  -  [ACRI06] <br> -  -  -  -  -  -  [ACRI07] <br> -  -  -  -  -  -  [ACRI08] <br> -  -  -  -  -  -  [ACRI09] <br> -  -  -  -  -  -  [ACRI10] <br> -  -  -  -  -  -  [ACRI11] <br> -  -  -  -  -  -  [ACRI12] <br> -  -  -  -  -  -  [ACRI13] <br> -  -  -  -  -  -  [ACRI14] <br> -  -  -  -  -  -  [ACRI15] <br> -  -  -  -  -  -  [ACRI16] <br> -  -  -  -  -  -  [ACRI17] <br> -  -  -  -  -  -  [ACRI18] <br> -  -  -  -  -  -  [ACRI19] <br> -  -  -  -  -  -  [ACRI20] <br> -  -  -  -  -  Tridactylidae <br> -  -  -  -  -  -  [TRID01] <br> -  -  -  -  -  -  [TRID02] <br> -  -  -  -  -  Trigonidiidae <br> -  -  -  -  -  -  [TRIG01] <br> -  -  -  -  -  -  [TRIG02] <br> -  -  -  -  -  -  [TRIG03] <br> -  -  -  -  -  -  [TRIG04] <br> -  -  -  -  -  -  [TRIG05] <br> -  -  -  -  -  -  [TRIG06] <br> -  -  -  -  -  Tetrigidae <br> -  -  -  -  -  -  [TETR03] <br> -  -  -  -  -  -  [TETR04] <br> -  -  -  -  -  -  [TETR05] <br> -  -  -  -  -  -  [TETR06] <br> -  -  -  -  -  -  [TETR07] <br> -  -  -  -  -  -  [TETR09] <br> -  -  -  -  -  -  [TETR10] <br> -  -  -  -  -  -  [TETR11] <br> -  -  -  -  -  -  [TETR12] <br> -  -  -  -  -  -  [TETR13] <br> -  -  -  -  -  -  [TETR14] <br> -  -  -  -  -  -  [TETR15] <br> -  -  -  -  -  -  [TETR16] <br> -  -  -  -  -  -  [TETR17] <br> -  -  -  -  -  -  [TETR18] <br> -  -  -  -  -  -  [TETR20] <br> -  -  -  -  -  -  [TETR21] <br> -  -  -  -  -  -  <i>Eucriotettix</i> <br> -  -  -  -  -  -  -  [TETR01] <br> -  -  -  -  -  -  <i>Cladonotella</i> <br> -  -  -  -  -  -  -  [TETR19] <br> -  -  -  -  -  -  <i>Boczkitettix</i> <br> -  -  -  -  -  -  -  <i>Boczkitettix borneensis</i> <br> -  -  -  -  -  -  <i>Paratettix</i> <br> -  -  -  -  -  -  -  <i>Paratettix variabilis</i> (as homotypic_synonym: <i>Euparatettix variabilis</i>)<br> -  -  -  -  -  Mogoplistidae <br> -  -  -  -  -  -  [MOGO01] <br> -  -  -  -  -  -  [MOGO02] <br></div><p></p>
Hornbill abundance and breeding incidence in relation to habitat modification and fig fruit availability
Open the record for dataset details and reuse information.
Data from: Reptile responses to anthropogenic habitat modification: a global meta-analysis
Aim <p>To determine how reptile populations respond to anthropogenic habitat modification and determine if species traits and environmental factors influence such responses.</p> Location <p>Global.</p> Time period <p>1981–2018.</p> Major taxa studied <p>Squamata.</p> Methods <p>We compiled a database of 56 studies reporting how habitat modification affects reptile abundance, and calculated standardised mean differences in abundance (Hedges' g). We used Bayesian meta-analytical models to test whether responses to habitat modification depended on body size, clutch size, reproductive mode, habitat specialisation, range size, disturbance type, vegetation type, temperature and precipitation.</p> Results <p>Based on 815 effect sizes from 376 species, we found an overall negative effect of habitat modification on reptile abundance (mean Hedges' g = -0.43, 95% credible intervals = -0.61 to -0.26). Reptile abundance was, on average, one-third lower in modified compared to unmodified habitats. Small range sizes and small clutch sizes were associated with more negative responses to habitat modification, although the responses were weak and the credible intervals overlapped zero. We detected no effects of body size, habitat specialisation, reproductive mode (egg-laying or live-bearing), temperature, or precipitation. Some families exhibited more negative responses than others, although overall there was no phylogenetic signal in the data. Mining had the most negative impacts on reptile abundance, followed by agriculture, grazing, plantations and patch size reduction, whereas the mean effect of logging was neutral.</p> Main conclusions <p>Habitat modification is a key cause of reptile population declines, although there is variability in responses both within and between species, families, and vegetation types. The effect of disturbance type appeared to be related to intensity of habitat modification. Ongoing development of environmentally sustainable practices that ameliorate anthropogenic impacts is urgently needed to prevent reptile population declines.</p>
Singing under glass: rapid effects of anthropogenic habitat modification on song and response behaviours in an isolated house sparrow (Passer domesticus) population
<p>Anthropogenic noise pollution and the introduction of novel infrastructure can impose strong selective pressures on avian communication by affecting the efficacy with which acoustic signals are transmitted and received. Many species have now been shown to sing at higher frequencies in noisy urban environments. However, few studies have investigated the effects of signal modification on the response behaviours of receivers, and fewer still have been able to indicate the timescale over which these changes in pitch have occurred. We compare vocal communication between house sparrows (Passer domesticus) that reside within the world's largest, single-span glasshouse (completed in the year 2000), and house sparrows directly outside this glasshouse, in open farmland. The glasshouse contrasts both acoustically and physically with the external environment, low frequency background noise being significantly louder inside than outside. We show that minimum song frequency was significantly higher inside the glasshouse than in surrounding farm habitat. Using song playback, we also found that birds within the glasshouse reacted more strongly to playbacks from the glasshouse habitat than they did to playback of song from farm birds outside. The degree of difference in frequency is similar to that shown for other bird species between urban and rural environments, demonstrating that such behavioural differences may arise over a relatively short time period (14 years in this case)</p>
Data for: Living fast, dying young: anthropogenic habitat modification influences the fitness and life history traits of a cooperative breeder
<p>Datasets and scripts for the study: Living fast, dying young: anthropogenic habitat modification influences the fitness and life history traits of a cooperative breeder</p>
Data from: Genome-wide analysis reveals demographic and life history patterns associated with habitat modification in land-locked, deep-spawning sockeye salmon (Oncorhynchus nerka)
<p>Human-mediated habitat fragmentation in freshwater ecosystems can negatively impact genetic diversity, demography and life history of native biota, while disrupting the behaviour of species that are dependent on spatial connectivity to complete their life cycles. In the Alouette River system (British Columbia, Canada), dam construction in 1928 impacted passage of anadromous sockeye salmon (<i>Oncorhynchus nerka</i>), with the last records of migrants occurring in the 1930's. Since that time, <i>O. nerka</i> persisted as a resident population in Alouette Reservoir until experimental water releases beginning in 2005 created conditions for migration; two years later, returning migrants were observed for the first time in ~70 years, raising important basic and applied questions regarding life history variation and population structure in this system. Here, we investigated the genetic distinctiveness and population history of Alouette Reservoir <i>O. nerka</i> using genome-wide SNP data (n=7,709 loci) collected for resident and migrant individuals, as well as for neighbouring anadromous sockeye salmon and resident kokanee populations within the Fraser River drainage (n=312 individuals). Bayesian clustering and principal components analyses based on neutral loci revealed five distinct clusters, largely associated with geography, and clearly demonstrated that Alouette Reservoir resident and migrant individuals are genetically distinct from other <i>O. nerka</i> populations in the Fraser River drainage. At a finer-level, there was no clear evidence for differentiation between Alouette Reservoir residents and migrants; although we detected eight high-confidence outlier loci, they all mapped to sex chromosomes suggesting that differences were likely due to uneven sex ratios rather than life history. Taken together, these data suggest that contemporary Alouette Reservoir <i>O. nerka</i> represents a landlocked sockeye salmon population, constituting the first reported instance of deep-water spawning behaviour associated with this life history form. This finding punctuates the need for re-assessment of conservation status and supports on-going fisheries management activities in Alouette Reservoir. </p>
Data from: Reptile responses to anthropogenic habitat modification: a global meta-analysis
Open the record for dataset details and reuse information.
Data from: Genome-wide analysis reveals demographic and life history patterns associated with habitat modification in land-locked, deep-spawning sockeye salmon (Oncorhynchus nerka)
Open the record for dataset details and reuse information.
Singing under glass: rapid effects of anthropogenic habitat modification on song and response behaviours in an isolated house sparrow (Passer domesticus) population
Open the record for dataset details and reuse information.
Data from: Competition-driven build-up of habitat isolation and selection favouring dispersal modification in a young avian hybrid zone
Competition-driven evolution of habitat isolation is an important mechanism of ecological speciation but empirical support for this process is often indirect. We examined how an on-going displacement of pied flycatchers from their preferred breeding habitat by collared flycatchers in a young secondary contact zone is associated with (a) access to an important food resource (caterpillar larvae), (b) immigration of pied flycatchers in relation to habitat quality, and (c) the risk of hybridization in relation to habitat quality. Over the past 12 years, the estimated access to caterpillar larvae biomass in the habitat surrounding the nests of pied flycatchers has decreased by a fifth due to shifted establishment possibilities, especially for immigrants. However, breeding in the high quality habitat has become associated with such a high risk of hybridization for pied flycatchers that overall selection currently favors pied flycatchers that were forced to immigrate into the poorer habitats (despite lower access to preferred food items). Our results show that competition-driven habitat segregation can lead to fast habitat isolation, which per se caused an opportunity for selection to act in favor of future "voluntarily" altered immigration patterns and possibly strengthened habitat isolation through reinforcement.
Supporting data for Boron and Deere et al. (Current Biology, 2023): "Habitat modification destabilizes spatial associations and persistence of Neotropical carnivores"
<p>Data underpinning the Current Biology publication "Habitat modification destabilizes spatial associations and persistence of Neotropical carnivores" (doi.org/10.1016/j.cub.2023.07.064). Species detection data for 11 Neotropical carnivores obtained using camera trap methods across a gradient of human habitat modification. Cameras were deployed across 468 sampling locations distributed across nine study landscapes in Colombia. Site-level covariates detailing forest extent, habitat quality and proximity to key environmental resources are also provided. These data were implemented to assess spatial associations between sympatric carnivores across gradients of human habitat modification. </p>
Data from: Competition-driven build-up of habitat isolation and selection favouring dispersal modification in a young avian hybrid zone
Open the record for dataset details and reuse information.
Anthropogenic habitat modification causes nonlinear multiscale bird diversity declines
<p>Anthropogenic habitat modification is a leading contributor to biodiversity change, but it is unclear what factors, including scale, influence the magnitude of change. Changes in species richness and its scaling relationship across an anthropogenic gradient can be influenced by changes in the total number of individuals in each sample, the species abundance distribution, and/or the spatial arrangement of conspecific individuals. Here, we integrated continental-scale citizen science data on bird occurrences across the contiguous United States — from eBird — with an analytical framework capable of dissecting<em> </em>the aforementioned biodiversity components to quantify bird diversity changes along an anthropogenic landscape habitat modification gradient. We found an overall decline in bird diversity along an anthropogenic modification gradient, with peak levels of bird diversity at low to moderate levels of modification. The magnitude of biodiversity change was greater at gamma than at alpha scales and was most strongly associated with a declining number of individuals along the anthropogenic gradient. Spatial species turnover was lower at higher impacted sites, but this was also due to the sampling of fewer individuals rather than changes in spatial species patchiness. Our results suggest that local-scale management can promote bird diversity, especially at the natural-rural-suburban interface. Management efforts (e.g., managing natural habitat or preserving urban greenspaces against development) should be focused on creating, restoring, and preserving resources (e.g., nesting habitat, foraging resources) necessary for a large number of individuals, as this is the primary influence of diversity change along an anthropogenic gradient.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.